Literature DB >> 30238276

Pathologic findings in reduction mammoplasty specimens: a surrogate for the population prevalence of breast cancer and high-risk lesions.

Francisco Acevedo1, V Diego Armengol1, Zhengyi Deng1, Rong Tang1, Suzanne B Coopey1, Danielle Braun2,3, Adam Yala1,2,3,4, Regina Barzilay1,2,3,4, Clara Li1,2,3,4, Amy Colwell1, Anthony Guidi1, Curtis L Cetrulo1, Judy Garber2, Barbara L Smith1, Tari King1, Kevin S Hughes5.   

Abstract

PURPOSE: Mammoplasty removes random samples of breast tissue from asymptomatic women providing a unique method for evaluating background prevalence of breast pathology in normal population. Our goal was to identify the rate of atypical breast lesions and cancers in women of various ages in the largest mammoplasty cohort reported to date.
METHODS: We analyzed pathologic reports from patients undergoing bilateral mammoplasty, using natural language processing algorithm, verified by human review. Patients with a prior history of breast cancer or atypia were excluded.
RESULTS: A total of 4775 patients were deemed eligible. Median age was 40 (range 13-86) and was higher in patients with any incidental finding compared to patients with normal reports (52 vs. 39 years, p = 0.0001). Pathological findings were detected in 7.06% (337) of procedures. Benign high-risk lesions were found in 299 patients (6.26%). Invasive carcinoma and ductal carcinoma in situ were detected in 15 (0.31%) and 23 (0.48%) patients, respectively. The rate of atypias and cancers increased with age.
CONCLUSION: The overall rate of abnormal findings in asymptomatic patients undergoing mammoplasty was 7.06%, increasing with age. As these results are based on random sample of breast tissue, they likely underestimate the prevalence of abnormal findings in asymptomatic women.

Entities:  

Keywords:  Breast; Breast diseases; Breast neoplasm; Epidemiology; Mammaplasty

Mesh:

Year:  2018        PMID: 30238276     DOI: 10.1007/s10549-018-4962-0

Source DB:  PubMed          Journal:  Breast Cancer Res Treat        ISSN: 0167-6806            Impact factor:   4.872


  4 in total

Review 1.  Use of Natural Language Processing to Extract Clinical Cancer Phenotypes from Electronic Medical Records.

Authors:  Guergana K Savova; Ioana Danciu; Folami Alamudun; Timothy Miller; Chen Lin; Danielle S Bitterman; Georgia Tourassi; Jeremy L Warner
Journal:  Cancer Res       Date:  2019-08-08       Impact factor: 12.701

Review 2.  Extragenital lichen sclerosus: a comprehensive review of clinical features and treatment.

Authors:  Aaron Burshtein; Joshua Burshtein; Sergey Rekhtman
Journal:  Arch Dermatol Res       Date:  2022-10-05       Impact factor: 3.033

3.  Pathology Examination of Breast Reduction Specimens: Dispelling the Myth.

Authors:  Mark Fisher; Aaron L Burshtein; Joshua G Burshtein; Panagiotis Manolas; Scot B Glasberg
Journal:  Plast Reconstr Surg Glob Open       Date:  2020-11-24

4.  Discussion of Histopathological Findings of 954 Breast Reduction Specimens.

Authors:  Soysal Bas; Cagatay Oner; Ali Can Aydin; Ramazan Ucak; Selami Serhat Sirvan; Semra Karsidag
Journal:  Sisli Etfal Hastan Tip Bul       Date:  2021-03-17
  4 in total

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